Bo FreseAgentic AI Development
in Practice
What it actually takes to use AI on a codebase that matters. One day, hands-on, for experienced developers who are ready for the next step.
Image created with AI - obviously :-)
What this course is about
What happens when you let AI loose on your real codebase? Not a toy project. Not a browser chat window. Your actual code, your actual architecture, an AI that acts across dozens of files and hundreds of decisions.
That is what this course is about - the discipline, structure, and understanding that separates professional AI-assisted development from experimental use. We use Claude Code as our example tool, but the same principles apply across GitHub Copilot, OpenAI Codex, and most other agentic tools that run directly on your machine.
You leave with something you've built, a clear methodology, and concrete tools to build the frameworks your organisation needs.
What you will learn
After the course, you will be able to:
- Set up an agentic AI development tool and use it professionally — not just experimentally
- Design and structure context so AI solves the right problem the right way
- Build your own skills and commands tailored to your workflow and technical context
- Use AI as a thinking partner from vision and requirements to finished code
- Establish a test and review discipline that keeps a human accountable for the code
The course is not a list of prompts to copy. It's a way of thinking you take back and adapt to your own context.
— Bo Frese
Course programme
Five modules, alternating between teaching, demo, and hands-on exercises. The day is structured so each module builds on the last.
- Module 1 — What changes when AI touches your codebase? The right mental model. An agentic AI tool is not a chat window — it's an agent acting autonomously across many steps. Risk, responsibility, and why undisciplined AI use doesn't scale on professional projects.
- Module 2 — Context engineering The most underrated discipline in AI-assisted development. CLAUDE.md and its equivalents, context architecture, and why different tasks require different context. Walkthrough of a complete professional toolkit.
- Module 3 — AI as thinking partner From vision and business model to requirements, architecture, and design. How to get honest answers instead of confirmation. Prompt design that invites criticism and surfaces blind spots.
- Module 4 — Code quality and review discipline When AI writes the code, you need to think differently about testing and review. BDD over implementation tests. Code review with AI: how to understand and take ownership of code you didn't write.
- Module 5 — Building the framework for your organisation From personal toolkit to team standard. Custom commands that reflect your methodology and context. Warning signs. The quality conversations your organisation needs to have before scaling AI use.
Practical information
Format: One day (9:00–17:00), teaching alternates with hands-on exercises. Available in Danish and English.
Delivery: Primarily as in-house training at your premises. Content and focus can be aligned to your technological context, adjusted in length, or combined into a longer programme.
Who it's for: Experienced software developers — minimum mid-level. This course is not about learning to code. It's about learning to work with AI as a professional development partner.
What to bring: A laptop with your agentic AI tool installed and ready. A small hobby or side project to work on during exercises. A Claude Pro subscription is likely sufficient — the course alternates between theory, demo, and hands-on work, so you won't be burning tokens all day.
About the instructor
I'm a software developer with 35 years of experience — as a developer, architect, team lead, startup founder, and product owner. I still build products today.
A year of intensive AI-assisted development changed how I work fundamentally — and made clear what goes wrong when organisations are seduced by how convincing it looks. This course draws directly from that experience. Not theory. Not research. What actually happened, and what I'd do differently.
In the end, it's developers who have to stand behind the quality of what gets built. That's what this course is about.